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Author | Adriana Romero; Petia Radeva; Carlo Gatta | ||||
Title | Meta-parameter free unsupervised sparse feature learning | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 37 | Issue | 8 | Pages | 1716-1722 |
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Abstract | We propose a meta-parameter free, off-the-shelf, simple and fast unsupervised feature learning algorithm, which exploits a new way of optimizing for sparsity. Experiments on CIFAR-10, STL- 10 and UCMerced show that the method achieves the state-of-theart performance, providing discriminative features that generalize well. | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | MILAB; 600.068; 600.079; 601.160 | Approved | no | ||
Call Number | Admin @ si @ RRG2014b | Serial | 2594 | ||
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Author | Adriana Romero; Petia Radeva; Carlo Gatta | ||||
Title | No more meta-parameter tuning in unsupervised sparse feature learning | Type | Miscellaneous | ||
Year | 2014 | Publication | Arxiv | Abbreviated Journal | |
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Abstract | CoRR abs/1402.5766
We propose a meta-parameter free, off-the-shelf, simple and fast unsupervised feature learning algorithm, which exploits a new way of optimizing for sparsity. Experiments on STL-10 show that the method presents state-of-the-art performance and provides discriminative features that generalize well. |
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Address | |||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | MILAB; LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RRG2014 | Serial | 2471 | ||
Permanent link to this record |